Brain-machine interactions for assessing the dynamics of neural systems

Michael Kositsky, Michela Chiappalone, Simon T. Alford, Ferdinando A. Mussa-Ivaldi*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

12 Scopus citations


A critical advance for brain-machine interfaces is the establishment of bi-directional communications between the nervous system and external devices. However, the signals generated by a population of neurons are expected to depend in a complex way upon poorly understood neural dynamics. We report a new technique for the identifi cation of the dynamics of a neural population engaged in a bi-directional interaction with an external device. We placed in vitro preparations from the lamprey brainstem in a closed-loop interaction with simulated dynamical devices having different numbers of degrees of freedom. We used the observed behaviors of this composite system to assess how many independent parameters - or state variables - determine at each instant the output of the neural system. This information, known as the dynamical dimension of a system, allows predicting future behaviors based on the present state and the future inputs. A relevant novelty in this approach is the possibility to assess a computational property - the dynamical dimension of a neuronal population - through a simple experimental technique based on the bi-directional interaction with simulated dynamical devices. We present a set of results that demonstrate the possibility of obtaining stable and reliable measures of the dynamical dimension of a neural preparation.

Original languageEnglish (US)
Article numberArticle 1
JournalFrontiers in Neurorobotics
Issue numberMAR
StatePublished - 2009


  • Closed-loop system
  • Dynamical dimension
  • Lamprey brainstem
  • Simulated dynamical device

ASJC Scopus subject areas

  • Biomedical Engineering
  • Artificial Intelligence


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